---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_finetune_race_20
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# llama_finetune_race_20

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4534

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2478        | 1.0   | 150  | 1.4180          |
| 0.7183        | 2.0   | 300  | 1.4867          |
| 0.5553        | 3.0   | 450  | 1.6282          |
| 0.6139        | 4.0   | 600  | 1.8190          |
| 0.2089        | 5.0   | 750  | 1.9858          |
| 0.1597        | 6.0   | 900  | 2.1239          |
| 0.1706        | 7.0   | 1050 | 2.2716          |
| 0.1075        | 8.0   | 1200 | 2.4046          |
| 0.0903        | 9.0   | 1350 | 2.5014          |
| 0.0755        | 10.0  | 1500 | 2.5739          |
| 0.0686        | 11.0  | 1650 | 2.7048          |
| 0.0547        | 12.0  | 1800 | 2.6282          |
| 0.0495        | 13.0  | 1950 | 2.8231          |
| 0.0455        | 14.0  | 2100 | 3.0115          |
| 0.0415        | 15.0  | 2250 | 3.0576          |
| 0.0436        | 16.0  | 2400 | 3.2100          |
| 0.048         | 17.0  | 2550 | 3.3084          |
| 0.0396        | 18.0  | 2700 | 3.3839          |
| 0.0402        | 19.0  | 2850 | 3.4183          |
| 0.036         | 20.0  | 3000 | 3.4534          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1